Abstract: Landslides pose a significant threat to human life, infrastructure, and the environment, particularly in hilly and mountainous regions. Early detection and timely warnings are crucial for minimizing damage and ensuring safety. This project proposes a cost-effective, real-time stability monitoring system for early landslide detection and risk mitigation using an IoT-based approach. The system utilizes a NodeMCU (ESP8266) microcontroller as the central processing and communication unit, interfaced with a soil moisture sensor, DHT11 sensor (for temperature and humidity), and a vibration sensor (such as SW-420).

These sensors continuously monitor key environmental parameters that influence slope stability, including soil saturation levels, ambient temperature and humidity, and ground vibrations. The collected data is transmitted wirelessly to a cloud platform or local server, where it can be monitored in real time. Threshold values are predefined for each sensor to identify critical conditions indicative of a potential landslide. Upon detecting abnormal readings—such as high soil moisture levels, rapid temperature changes, or sudden vibrations—the system triggers an alert mechanism (e.g., buzzer, SMS, or cloud notification), enabling timely evacuation or preventive actions.

The proposed system is designed to be low-cost, scalable, and suitable for deployment in remote or vulnerable areas. By integrating environmental sensing with IoT capabilities, this project demonstrates an effective and proactive approach to landslide risk management and disaster preparedness.

This wireless landslide detection system provides a real-time, automated, and reliable solution for early warning and disaster prevention, helping authorities and communities take timely preventive actions to minimize damage and save lives.

Keywords: Stability Monitoring System, Landslide Detection, Risk Mitigation, Soil Moisture Sensor, Tilt Sensor, Vibration Sensor, IoT Monitoring, Early Warning System, Slope Stability, Disaster Management.

Downloads: | DOI: 10.17148/IJIREEICE.2026.14329